Comparison of Different Models for Predicting Development Time of the European Corn Borer (Lepidoptera: Pyralidae)

Abstract

Nine nonlinear models (degree-day with a 10°C base, degree-day model, polynomial, normal distribution, Stinner model, Sharpe and DeMichele model, Logan model with or without a base, Hilbert and Logan model) were tested to describe the relationship between development rate and temperature for the European corn borer, Ostrinia nubilalis Hübner. These models were calibrated with laboratory experiments based on destructive sampling under sinusoidal temperatures from 9 to 42°C. They were then evaluated and compared with field experiments, at temperatures from 4 to 37°C, carried out as artificial infestations in various areas. Laboratory development models with the smallest time shifts between predicted and observed molts were the Sharpe and DeMichele model, polynomial model, normal distribution, and Stinner model. A classification with an adjusted coefficient of determination (taking into account the number of parameters in the model) slightly modified the results and the best models were the polynomial and the normal distribution, followed by the Stinner model and the degree-day model with a 10°C base. The classification was almost reversed under field conditions. Large shifts occurred in all models in some experiments, thereby demonstrating that temperature was not the only factor involved. Models showing the smallest shifts under field conditions were the degree-day model and the Logan model. The experiments that showed the greater shifts corresponded to infestations on early or on late phenological stages of corn. Results confirmed that the experimental design and calibration method were adequate. The laboratory experiments provided a means of calibrating the models and of predicting results under field conditions from laboratory experiments. Future studies will focus on a precise quantitative analysis of factors affecting development other than temperature, notably infestation date, climatic factors, and phenological stage of corn.